New cooperative projection neural network for nonlinearly constrained variational inequality

作     者：XIA YouSheng 

作者机构：College of Mathematics and Computer Science Fuzhou University Fuzhou 350108 China 

基　　金：Supported by the National Natural Science Foundation of China (Grant No. 60875085) the Natural Science Foundation of Fujian Province(Grant No. 2008J0019) 

出 版 物：《Science in China(Series F)》 (中国科学（F辑英文版）)

年 卷 期：2009年第52卷第10期

页      码：1766-1777页

摘      要：This paper proposes a new cooperative projection neural network （CPNN）, which combines automatically three individual neural network models with a common projection term. As a special case, the proposed CPNN can include three recent recurrent neural networks for solving monotone variational inequality problems with limit or linear constraints, respectively. Under the monotonicity condition of the corresponding Lagrangian mapping, the proposed CPNN is theoretically guaranteed to solve monotone variational inequality problems and a class of nonmonotone variational inequality problems with linear and nonlinear constraints. Unlike the extended projection neural network, the proposed CPNN has no limitation on the initial point for global convergence. Compared with other related cooperative neural networks and numerical optimization algorithms, the proposed CPNN has a low computational complexity and requires weak convergence conditions. An application in real-time grasping force optimization and examples demonstrate good performance of the proposed CPNN.

主 题 词：variational inequality problems general constraints cooperative recurrent neural network complexity global convergence conditions 

学科分类：12[管理学] 1201[管理学-管理科学与工程类] 07[理学] 081104[081104] 08[工学] 0835[0835] 0701[理学-数学类] 0811[工学-水利类] 070101[070101] 0812[工学-测绘类] 

核心收录：

D　O　I：10.1007/s11432-009-0168-8

馆 藏 号：203471880...